Presented September 21, 2015.
This session is about the surveillance R package as a tool for performing prospective outbreak detection in routine collected surveillance data. Michael Höhle will discuss the data structure, invocation of implemented outbreak detection methods as well as visualization. Finally, he shall give a small outlook to handling reporting delays (nowcasting & delay-adjusted outbreak detection). Focus of the session will be on problems and R code and, hence, less on the statistical methods.
A source for additional information before/after the talk is the report 'Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance', arxiv.org/abs/1411.1292, which is to appear in the Journal of Statistical Software.